E. Sherafat

D.K. Wells, K. Dang, ..., E. Sherafat, ...,I.I. Mandoiu, ..., S. Al Seesi,..., and N.A.Defranoux, Strategies to improve the sensitivity and ranking ability of neoantigen prediction methods: Report on the results of the Tumor nEoantigen SeLection Alliance (TESLA), Advances in Cancer Immunotherapy, Virtual Keystone Symposium, Aug 18, 2020, url

D.K. Wells, K. Dang, ..., E. Sherafat, ...,I.I. Mandoiu, ..., S. Al Seesi,..., and N.A.Defranoux, Strategies to improve the sensitivity and ranking ability of neoantigen prediction methods: Report on the results of the Tumor nEoantigen SeLection Alliance (TESLA), Poster at AACR Annual Meeting 2020, June 22-24, 2020, url

E. Sherafat and J. Force and I.I Mandoiu, Positive-Unlabeled Learning for Cancer Neoepitope Identification, 8th Workshop on Computational Advances in Molecular Epidemiology, Niagara Falls, NY, Sept. 7, 2019, ppt, url

E. Sherafat and I.I. Mandoiu, PU-Caller: Sensitive somatic variant calling using positive-unlabeled learning, 15th International Symposium on Bioinformatics Research and Applications, Barcelona, Spain, June 3-6, 2019, ppt, url

H. Ebrahimi-Nik and T. Shcheglova and J. Michaux and H. Pak and E. Sherafat and S. Al Seesi and I.I. Mandoiu and M. Bassani-Sternberg and P.K. Srivastava, Mass spectroscopy-defined neoepitopes are a rich source of tumor rejection-mediating neoepitopes in a mouse sarcoma, IMMUNOLOGY 2019, San Diego CA, May 9–13, 2019, url

E. Sherafat and I.I. Mandoiu, PU-Caller: Sensitive Somatic Variant Calling Using Positive-Unlabeled Learning, Poster at 23rd Annual International Conference on Research in Computational Molecular Biology (RECOMB), Washington, DC, May 5-8, 2019, ppt, url

E. Sherafat and I.I. Mandoiu, Application of clustering to identify different cell types from single-cell transcriptomes, Poster at 11th International Symposium on Bioinformatics Research and Applications, Norfolk, VA, June 7-10, 2015, ppt, url